Ed Note: Gideon is speaking at ODSC Europe 2019, see his talk "Augmented Programming" there. Over the past decade, deep learning research has led to significant advances in perceptual tasks, such as object detection, face recognition, and speech recognition. In each of these use cases, raw real-world inputs have to be mapped into a normalized representation. Deep learning has also started to lead to significant advances in natural language processing, for example, where contextual embeddings enable multi-task transfer learning. A newer, emerging field for machine learning is in its application within the production, deployment, and maintenance of software.

Handwriting is becoming a rare skill in the digital age. But researchers have now discovered a new application that could significantly improve the way tetraplegic people, who are often also unable to speak, communicate with the outside world. At the Society for Neuroscience's annual meeting in Chicago this week, a team of neurologists presented a new tool that could read out the sentences formed by a volunteer paralyzed from the neck down, in double the average speed recorded for existing technologies. The volunteer's imagination: he was asked to imagine that he was moving his arm to hand-write each letter of the alphabet, one at a time, with an imaginary pencil. Writing, since it's a movement, requires a certain cerebral organization that has already been located in previous studies as happening in the primary motor cortex.

AI is no longer just a research project. It's solving real-world problems for organizations, which now need to figure out where to deploy their AI models to make faster decisions. With the convergence of AI, the Internet of Things and the approaching 5G infrastructure, the opportunity is ripe for companies to push their models beyond the data center to the edge, where billions of sensors are streaming data and making real-time decisions is a reality. Enterprises deploying AI workloads at scale are using a combination of on-premises data centers and the cloud, bringing the AI models to where the data is being collected. Deploying these workloads at the edge, say in a retail store or parking garage, can be very challenging if IT expertise is not available as one might have with data centers.

Facebook AI Research says it's created a machine learning system for de-identification of individuals in video. Startups like D-ID and a number of previous works have made de-identification technology for still images, but this is the first one that works on video. In initial tests, the method was able to thwart state-of-the-art facial recognition systems. The AI for automatic video modification doesn't need to be retrained to be applied to each video. It maps a slightly distorted version on a person's face in order to make it difficult for facial recognition technology to identify a person.

Rex Mundi is a comic book, a Johnny Depp adaption of such and a DJ. Vincent Peters, with a board of directors deriving experience from careers at Google, Facebook and SpaceX, wants his startup to be king of sports betting predictive analysis when the artificial intelligence-based system launches to the public later this year. In a crowded market where data analysts and other AI-wielding outfits are rushing in to exploit the methodical spread of legal sports betting across the United States, innovation and results will be crucial. Peters said Rex Mundi, which he founded, is producing a "65-to-68%" accuracy rate but added "we're looking for ways to get it up to 70%." Experience and leadership will matter also, Peters believes, leading the company to add DHL Express America CEO Mike Parra to a board of directors on Wednesday that includes former American Apparel CEO Chelsea Grayson. "Rex Mundi's unique vision and cutting edge algorithm will bring a one-of-a-kind experience to the space," Parra said.

Researchers from the University of Texas at Austin (UT-Austin), Cornell Tech, Georgia Tech, and Facebook AI Research have created an artificial intelligence system that can be used to give personalized fashion advice, published here. Now one of the projects under UT-Austin's Department of Computer Science, Fashion, was created with a philosophy of making minimal changes to maximize outfit fashionability. According to a press release from the UT-Austin, the system analyzes several factors of outfits, such as the color, pattern, texture, and shape, and gives recommendations based on this analysis. The researchers posted a video summarizing how Fashion works. A key component of how the system works is in machine learning.

The corporate war to provide cloud computing for US warfighters is over. Late Friday, the Department of Defense announced that Microsoft has won the Joint Enterprise Defense Infrastructure contract, known as JEDI. The decision was the culmination of a two-year process that also included Google, IBM, and Oracle, and where Amazon was long seen as the favorite. JEDI, potentially worth $10 billion over 10 years, has been positioned by the Pentagon as crucial to modernizing its use of technology--and making the US military more deadly. "We must improve the speed and effectiveness with which we develop and deploy modernized technical capabilities to our women and men in uniform," DoD Chief Information Officer Dana Deasy said in a statement.

TOPSHOT - Irish rock band U2 singer Bono gestures at Lyon's city hall, central eastern France, on ... [ ] October 9, 2019, during the funding conference of Global Fund to Fight AIDS, Tuberculosis and Malaria. The fund has asked for $14 billion, an amount it says would help save 16 million lives, avert "234 million infections" and place the world back on track to meet the UN objective of ending the epidemics of HIV/AIDS, tuberculosis and malaria within 10 years. An FDA-cleared smart thermometer powered with artificial intelligence (AI) from Kinsa can estimate influenza-like illness across the US in real-time and predict a pattern three weeks before it's identified. To create a real-time illness-signal Kinsa aggregates tens of millions of anonymized data inputs from close to a million US households with a Kinsa thermometer and applies AI to triage illnesses based on severity, duration and contagiousness. From this data, Kinsa was able to create a real-time health map using their smart thermometer which serves as a geo-precise signal for tracking illness.

In recent years, technology has played a significant role in reshaping the landscape of college teaching, and it will surely continue to do so. But the groundswell of artificial intelligence (AI) that surrounds us marks a particularly fragile moment for teaching. In this context, educators must be especially mindful that our uses of technology do not undermine meaningful learning. And doing this requires knowledge about technology and teaching. That's because for many students, college is a pathway to prepare for the workforce or improve one's existing skills to advance a career.

Computer chipmaker and storage company Micron Technology Inc. is pitching its hardware for artificial intelligence workloads after acquiring a startup called FWDNXT. The company announced the acquisition at its annual Micron Insight conference in San Francisco today, describing FWDNXT as a provider of AI hardware and software for deep learning, which is a subset of AI that tries to mimic the way the human brain solves problems. Micron's plan is to integrate FWDNXT's technology with its own, optimized flash memory products to create what it says will be a "comprehensive AI development platform." "FWDNXT is an architecture designed to create fast-time-to-market edge AI solutions through an extremely easy to use software framework with broad modeling support and flexibility," Micron Executive Vice President and Chief Business Officer Sumit Sadana said in a statement. "FWDNXT's five generations of machine learning inference engine development and neural network algorithms, combined with Micron's deep memory expertise, unlocks new power and performance capabilities to enable innovation for the most complex and demanding edge applications."